Databricks is present in 13 markets with 13 products. Databricks has 885 reviews with an overall average rating of 4.6.
AI Agent Development Platforms for Software Engineering
Platforms enable developers to create and manage AI agents through code, configuration and metadata, offering flexibility and control for implementing complex logic and integrations. Many of the tools provide low-code, programmatic, or natural language development experiences. This category includes both low-code and pro-code offerings
Databricks has 1 product in AI Agent Development Platforms for Software Engineering market
Analytics Query Accelerators (Retired)
Analytics query accelerators provide SQL or SQL-like query support on a broad range of data sources. They are most frequently used as a means of providing interactive and production-optimized delivery on semantically flexible data stores that do not inherently have the capabilities to provide sufficient performance or ease of use on their own. Commonly used in conjunction with data lakes, they aim to support BI dashboards, interactive query capabilities, data modeling and other analytics use cases. (Retired as of Feb-26-2026).
Databricks has 1 product in Analytics Query Accelerators (Retired) market
Analytics and Business Intelligence Platforms
Gartner defines analytics and business intelligence platforms (ABI) as those that enable organizations to model, analyze and visualize data to support informed decision making and value creation. These platforms facilitate the preparation of data and the creation of interactive dashboards, reports and visualizations to uncover patterns, predict trends and optimize operations. By doing so, they empower users to collaborate and effectively communicate the dimensions and measures that drive their organization. The platforms may also optionally include the ability to create, modify or enrich a semantic model, including business rules. Analytics and business intelligence platforms integrate data from multiple sources, such as databases, spreadsheets, cloud services and external data feeds, to provide a unified view of data, breaking down silos and transforming raw data into meaningful insights. They also allow users to clean, transform and prepare data for analysis, in addition to creating data models that define relationships between different data entities.
Databricks has 1 product in Analytics and Business Intelligence Platforms market
Augmented Analytics (Transitioning to Analytics and Business Intelligence Platforms)
Augmented analytics uses AI to automate analytics workflows in platforms, contextualizing user interfaces with automated insights, generative storytelling explanations and collaborative exploration. Driven by machine learning (ML) and generative AI, augmented analytics enables natural language queries and personalized analytics catalogs. It democratizes advanced analytics with augmented data ingestion, data preparation, analytics content and DSML model development. It also curbs human biases and accelerates insights for diverse users.
Databricks has 1 product in Augmented Analytics (Transitioning to Analytics and Business Intelligence Platforms) market
Cloud AI Developer Services (Transitioning to AI Coding Agents and Cloud-Native Application Platforms)
Gartner defines cloud AI developer services (CAIDS) as cloud-hosted or containerized services and products that enable software developers who are not data science experts to use artificial intelligence (AI) models via APIs, software development kits (SDKs) or applications. Core capabilities include automated machine learning (autoML) including automated data preparation, automated feature engineering and automated model building, and model management and operationalization for language, vision and tabular use cases. Optional and important complementary capabilities include AI code models and assistants. Cloud AI developer services help organizations embed intelligence, such as AI and ML insights, into their applications. While that is what cloud AI developer services offer, it is more important to note how they accomplish this. These services democratize and increase the availability of AI and ML to software engineers through the automation and features offered. Traditional activities regarding data acquisition, data quality, feature engineering, algorithm selection and model training are augmented by the technology. Cloud AI developer services open up a world of possibilities for software engineers to build AI and ML production capabilities and features for enterprise-built applications.
Databricks has 1 product in Cloud AI Developer Services (Transitioning to AI Coding Agents and Cloud-Native Application Platforms) market
Cloud Database Management Systems
Gartner defines the market for cloud database management systems (DBMSs) as software products that store and manipulate data and are primarily delivered as platform as a service (PaaS) in the cloud. Cloud DBMSs may optionally be capable of running on-premises or in hybrid, multicloud or intercloud configurations. They can be used for transactional and/or analytical work. They typically persist data using a combination of proprietary and open components in a durable manner, enabling a full range of create, read, update and delete operations. They are used by application end users, designers, developers and operators of large database systems.
Databricks has 1 product in Cloud Database Management Systems market
Data Clean Rooms
Data clean rooms are secure environments where multiple parties can analyze and share data without exposing raw data to each other. They enable collaborative analysis while ensuring privacy, compliance with data protection regulations, and strict access controls. These rooms use privacy-enhancing technologies to anonymize or aggregate data, allowing companies to gain insights from combined datasets without compromising individual privacy or proprietary information. The typical users include advertisers, publishers, data providers, and tech companies seeking to perform joint data analysis for marketing, research, and business intelligence.
Databricks has 1 product in Data Clean Rooms market
Data Management Platforms
Gartner defines data management platforms as integrated, dynamic data environments for managing enterprise data with operational simplicity. DMPs bring different data management capabilities into a single platform, enabling technical and business users to efficiently manage data for operational, analytical and AI use cases. DMPs use shared metadata to automate data management activities, paving the way for more advanced data ecosystems. A DMP is a commercial solution from a single vendor for managing general-purpose data for an organization, unlike a customer data platform.
Databricks has 1 product in Data Management Platforms market
Data Marketplaces and Exchanges
Data marketplaces and exchanges provide infrastructure, transactional capabilities and services for consumers and providers of data assets. Marketplaces prioritize data monetization via one-time or recurring subscription transactions, while exchanges prioritize sharing. Internal data exchanges facilitate enterprise data sharing and remove silos to cross-organization data product provision and access. AI’s need for large, varied and specialized datasets to train models has increased the demand for greater convenience in data sharing, purchase and consumption. Although adoption remains in the early phases, they provide liquidity to the data products space, enabling the sale, purchase or exchange of data products with relative ease. They enable secure multi‑party collaboration across partners, suppliers, and regulators, supported by strong data governance frameworks that ensure lineage tracking, policy enforcement, and stewardship consistency. Data Marketplaces and Data Exchanges are typically used by data scientists, analysts, product strategists, and business teams who need high‑quality internal or external datasets for analytics, AI modeling, and decision‑making
Databricks has 1 product in Data Marketplaces and Exchanges market
Data Science and Machine Learning Platforms (Transitioning to AI Platforms For Data Science and Machine Learning)
Gartner defines a data science and machine learning platform as an integrated set of code-based libraries and low-code tooling. These platforms support the independent use and collaboration among data scientists and their business and IT counterparts, with automation and AI assistance through all stages of the data science life cycle, including business understanding, data access and preparation, model creation and sharing of insights. They also support engineering workflows, including the creation of data, feature, deployment and testing pipelines. The platforms are provided via desktop client or browser with supporting compute instances or as a fully managed cloud offering.
Databricks has 1 product in Data Science and Machine Learning Platforms (Transitioning to AI Platforms For Data Science and Machine Learning) market
DataOps Tools
Gartner defines DataOps as the collaborative data management practice focusing on improving communication, continuous integration, automation, observability and operations of data flows between data managers, data consumers, and their teams across the organization. DataOps tools connect and orchestrate data pipelines across heterogeneous systems. Data and analytics leaders are the buyers in this emerging market. The primary audience for DataOps tools is “data manager” personas like, data engineers, data integration developers, operations/incident analysts, database administrators and data architects. The secondary audience is “data consumer” personas like business analysts, business intelligence developers, data scientists and citizen roles (departmental users who are domain experts, but less technical).
Databricks has 1 product in DataOps Tools market
Generative AI Engineering
Generative AI (GenAI) engineering refers to the field of engineering that focuses on the development, implementation and optimization of generative AI models. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. By developing GenAI models, engineers can create new and innovative ways to generate content. The vendors in this segment are made up by incumbent and startup vendors covering full-model life cycle management, specifically adjusted to and catering to development, refinement and deployment of generative models (e.g., LLMs) and other GenAI artifacts in production applications. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.
Databricks has 1 product in Generative AI Engineering market
Generative AI Model Providers
Generative AI (GenAI) model providers focus on developing and providing generative AI technologies and make them available to other developers, businesses and general public through APIs or commercial licenses. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. This layer of vendors offers access to commercial or open-source foundation models such as LLMs and other types of generative algorithms (such as GANs, genetic/evolutionary algorithms or simulations). These models can be provided for developers to embed into their applications or be used as base models for fine-tuning customized models for their software offerings or internal enterprise use cases. This helps businesses gain the benefits of advanced generative AI technologies while avoiding the high costs, expertise requirements and time needed to develop these technologies in-house. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.
Databricks has 1 product in Generative AI Model Providers market